pnn: Probabilistic neural networks

The program pnn implements the algorithm proposed by
Specht (1990). It is written in the R statistical language. It
solves a common problem in automatic learning. Knowing a set of
observations described by a vector of quantitative variables,
we classify them in a given number of groups. Then, the
algorithm is trained with this datasets and should guess
afterwards the group of any new observation. This neural
network has the main advantage to begin generalization
instantaneously even with a small set of known observations. It
is delivered with four functions (learn, smooth, perf and
guess) and a dataset. The functions are documented with
examples and provided with unit tests.